Update app.py

app.py

@@ -22,88 +22,84 @@ model.to(device)
 processor = AutoProcessor.from_pretrained("DAMO-NLP-SG/VideoLLaMA3-7B", trust_remote_code=True)
 
 
-class VideoLLaMA3GradioInterface(object):
-
-    def __init__(self, device="cpu", example_dir=None, **server_kwargs):
-        self.device = device
-        self.server_kwargs = server_kwargs
-        
-        self.image_formats = ("png", "jpg", "jpeg")
-        self.video_formats = ("mp4",)
-
-        image_examples, video_examples = [], []
-        if example_dir is not None:
-            example_files = [
-                osp.join(example_dir, f) for f in os.listdir(example_dir)
-            ]
-            for example_file in example_files:
-                if example_file.endswith(self.image_formats):
-                    image_examples.append([example_file])
-                elif example_file.endswith(self.video_formats):
-                    video_examples.append([example_file])
-
-        with gr.Blocks() as self.interface:
-            gr.Markdown(HEADER)
-            with gr.Row():
-                chatbot = gr.Chatbot(type="messages", elem_id="chatbot", height=710)
-
-                with gr.Column():
-                    with gr.Tab(label="Input"):
-
-                        with gr.Row():
-                            input_video = gr.Video(sources=["upload"], label="Upload Video")
-                            input_image = gr.Image(sources=["upload"], type="filepath", label="Upload Image")
-
-                        if len(image_examples):
-                            gr.Examples(image_examples, inputs=[input_image], label="Example Images")
-                        if len(video_examples):
-                            gr.Examples(video_examples, inputs=[input_video], label="Example Videos")
-
-                        input_text = gr.Textbox(label="Input Text", placeholder="Type your message here and press enter to submit")
-
-                        submit_button = gr.Button("Generate")
-
-                    with gr.Tab(label="Configure"):
-                        with gr.Accordion("Generation Config", open=True):
-                            do_sample = gr.Checkbox(value=True, label="Do Sample")
-                            temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, label="Temperature")
-                            top_p = gr.Slider(minimum=0.0, maximum=1.0, value=0.9, label="Top P")
-                            max_new_tokens = gr.Slider(minimum=0, maximum=4096, value=2048, step=1, label="Max New Tokens")
-
-                        with gr.Accordion("Video Config", open=True):
-                            fps = gr.Slider(minimum=0.0, maximum=10.0, value=1, label="FPS")
-                            max_frames = gr.Slider(minimum=0, maximum=256, value=180, step=1, label="Max Frames")
-
-            input_video.change(self._on_video_upload, [chatbot, input_video], [chatbot, input_video])
-            input_image.change(self._on_image_upload, [chatbot, input_image], [chatbot, input_image])
-            input_text.submit(self._on_text_submit, [chatbot, input_text], [chatbot, input_text])
-            submit_button.click(
-                self._predict,
-                [
-                    chatbot, input_text, do_sample, temperature, top_p, max_new_tokens,
-                    fps, max_frames
-                ],
-                [chatbot],
-            )
-
-    def _on_video_upload(self, messages, video):
+example_dir = "./examples"
+image_formats = ("png", "jpg", "jpeg")
+video_formats = ("mp4",)
+
+image_examples, video_examples = [], []
+if example_dir is not None:
+    example_files = [
+        osp.join(example_dir, f) for f in os.listdir(example_dir)
+    ]
+    for example_file in example_files:
+        if example_file.endswith(image_formats):
+            image_examples.append([example_file])
+        elif example_file.endswith(video_formats):
+            video_examples.append([example_file])
+
+
+with gr.Blocks() as interface:
+    gr.Markdown(HEADER)
+    with gr.Row():
+        chatbot = gr.Chatbot(type="messages", elem_id="chatbot", height=710)
+
+        with gr.Column():
+            with gr.Tab(label="Input"):
+
+                with gr.Row():
+                    input_video = gr.Video(sources=["upload"], label="Upload Video")
+                    input_image = gr.Image(sources=["upload"], type="filepath", label="Upload Image")
+
+                if len(image_examples):
+                    gr.Examples(image_examples, inputs=[input_image], label="Example Images")
+                if len(video_examples):
+                    gr.Examples(video_examples, inputs=[input_video], label="Example Videos")
+
+                input_text = gr.Textbox(label="Input Text", placeholder="Type your message here and press enter to submit")
+
+                submit_button = gr.Button("Generate")
+
+            with gr.Tab(label="Configure"):
+                with gr.Accordion("Generation Config", open=True):
+                    do_sample = gr.Checkbox(value=True, label="Do Sample")
+                    temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, label="Temperature")
+                    top_p = gr.Slider(minimum=0.0, maximum=1.0, value=0.9, label="Top P")
+                    max_new_tokens = gr.Slider(minimum=0, maximum=4096, value=2048, step=1, label="Max New Tokens")
+
+                with gr.Accordion("Video Config", open=True):
+                    fps = gr.Slider(minimum=0.0, maximum=10.0, value=1, label="FPS")
+                    max_frames = gr.Slider(minimum=0, maximum=256, value=180, step=1, label="Max Frames")
+
+    input_video.change(_on_video_upload, [chatbot, input_video], [chatbot, input_video])
+    input_image.change(_on_image_upload, [chatbot, input_image], [chatbot, input_image])
+    input_text.submit(_on_text_submit, [chatbot, input_text], [chatbot, input_text])
+    submit_button.click(
+        _predict,
+        [
+            chatbot, input_text, do_sample, temperature, top_p, max_new_tokens,
+            fps, max_frames
+        ],
+        [chatbot],
+    )
+
+    def _on_video_upload(messages, video):
         if video is not None:
             # messages.append({"role": "user", "content": gr.Video(video)})
             messages.append({"role": "user", "content": {"path": video}})
         return messages, None
-
-    def _on_image_upload(self, messages, image):
+    
+    def _on_image_upload(messages, image):
         if image is not None:
             # messages.append({"role": "user", "content": gr.Image(image)})
             messages.append({"role": "user", "content": {"path": image}})
         return messages, None
-
-    def _on_text_submit(self, messages, text):
+    
+    def _on_text_submit(messages, text):
         messages.append({"role": "user", "content": text})
         return messages, ""
-
+    
     @spaces.GPU(duration=120)
-    def _predict(self, messages, input_text, do_sample, temperature, top_p, max_new_tokens,
+    def _predict(messages, input_text, do_sample, temperature, top_p, max_new_tokens,
                  fps, max_frames):
         if len(input_text) > 0:
             messages.append({"role": "user", "content": input_text})
@@ -120,58 +116,51 @@ class VideoLLaMA3GradioInterface(object):
                     contents.append(message["content"])
                 else:
                     media_path = message["content"][0]
-                    if media_path.endswith(self.video_formats):
+                    if media_path.endswith(video_formats):
                         contents.append({"type": "video", "video": {"video_path": media_path, "fps": fps, "max_frames": max_frames}})
-                    elif media_path.endswith(self.image_formats):
+                    elif media_path.endswith(image_formats):
                         contents.append({"type": "image", "image": {"image_path": media_path}})
                     else:
                         raise ValueError(f"Unsupported media type: {media_path}")
-
+    
         if len(contents):
             new_messages.append({"role": "user", "content": contents})
-
+    
         if len(new_messages) == 0 or new_messages[-1]["role"] != "user":
             return messages
-
+    
         generation_config = {
             "do_sample": do_sample,
             "temperature": temperature,
             "top_p": top_p,
             "max_new_tokens": max_new_tokens
         }
-
+    
         inputs = processor(
             conversation=new_messages,
             add_system_prompt=True,
             add_generation_prompt=True,
             return_tensors="pt"
         )
-        inputs = {k: v.to(self.device) if isinstance(v, torch.Tensor) else v for k, v in inputs.items()}
+        inputs = {k: v.to(device) if isinstance(v, torch.Tensor) else v for k, v in inputs.items()}
         if "pixel_values" in inputs:
             inputs["pixel_values"] = inputs["pixel_values"].to(torch.bfloat16)
-
+    
         streamer = TextIteratorStreamer(processor.tokenizer, skip_prompt=True, skip_special_tokens=True)
         generation_kwargs = {
             **inputs,
             **generation_config,
             "streamer": streamer,
         }
-
+    
         thread = Thread(target=model.generate, kwargs=generation_kwargs)
         thread.start()
-
+    
         messages.append({"role": "assistant", "content": ""})
         for token in streamer:
             messages[-1]['content'] += token
             yield messages
 
-    def launch(self):
-        self.interface.launch(**self.server_kwargs)
-
 
 if __name__ == "__main__":
-    interface = VideoLLaMA3GradioInterface(
-        device=device,
-        example_dir="./examples",
-    )
     interface.launch()